Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-23T10:56:35.327Z Has data issue: false hasContentIssue false
  • English
  • Français

MICEmi: A method to identify cognitive endophenotypes of mental illnesses

Published online by Cambridge University Press:  28 November 2022

Patricia Correa-Ghisays Open the ORCID record for Patricia Correa-Ghisays [Opens in a new window] ,
Joan Vicent Sánchez-Ortí Open the ORCID record for Joan Vicent Sánchez-Ortí [Opens in a new window] ,
Vicent Balanzá-Martínez ,
Inmaculada Fuentes-Durá Open the ORCID record for Inmaculada Fuentes-Durá [Opens in a new window] ,
Anabel Martinez-Aran Open the ORCID record for Anabel Martinez-Aran [Opens in a new window] ,
Lara Ruiz-Bolo Open the ORCID record for Lara Ruiz-Bolo [Opens in a new window] ,
Paulina Correa-Estrada ,
Juan Carlos Ruiz-Ruiz Open the ORCID record for Juan Carlos Ruiz-Ruiz [Opens in a new window] ,
Gabriel Selva-Vera  and
Joan Vila-Francés Open the ORCID record for Joan Vila-Francés [Opens in a new window]
...Show all authors
Patricia Correa-Ghisays*
Affiliation:
Center for Biomedical Research in Mental Health Network (CIBERSAM), ISCIII, Madrid, Spain Department of Personality, Evaluation and Psychological Treatment, Faculty of Psychology, University of Valencia, Valencia, Spain INCLIVA Biomedical Research Institute, Valencia, Spain TMAP Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, Department of Medicine, University of Valencia, Valencia, Spain
Joan Vicent Sánchez-Ortí
Affiliation:
Department of Personality, Evaluation and Psychological Treatment, Faculty of Psychology, University of Valencia, Valencia, Spain INCLIVA Biomedical Research Institute, Valencia, Spain TMAP Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, Department of Medicine, University of Valencia, Valencia, Spain
Vicent Balanzá-Martínez*
Affiliation:
Center for Biomedical Research in Mental Health Network (CIBERSAM), ISCIII, Madrid, Spain INCLIVA Biomedical Research Institute, Valencia, Spain TMAP Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, Department of Medicine, University of Valencia, Valencia, Spain Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
Inmaculada Fuentes-Durá
Affiliation:
Center for Biomedical Research in Mental Health Network (CIBERSAM), ISCIII, Madrid, Spain Department of Personality, Evaluation and Psychological Treatment, Faculty of Psychology, University of Valencia, Valencia, Spain INCLIVA Biomedical Research Institute, Valencia, Spain TMAP Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, Department of Medicine, University of Valencia, Valencia, Spain
Anabel Martinez-Aran
Affiliation:
Center for Biomedical Research in Mental Health Network (CIBERSAM), ISCIII, Madrid, Spain Bipolar Disorders Unit, Neurosciences Institute, Hospital Clínic de Barcelona, IDIBAPS, Universitat de Barcelona, Catalonia, Spain
Lara Ruiz-Bolo
Affiliation:
Department of Personality, Evaluation and Psychological Treatment, Faculty of Psychology, University of Valencia, Valencia, Spain
Paulina Correa-Estrada
Affiliation:
Faculty of Psychology, EAFIT University, Medellín, Colombia
Juan Carlos Ruiz-Ruiz
Affiliation:
Department of Personality, Evaluation and Psychological Treatment, Faculty of Psychology, University of Valencia, Valencia, Spain
Gabriel Selva-Vera
Affiliation:
Center for Biomedical Research in Mental Health Network (CIBERSAM), ISCIII, Madrid, Spain INCLIVA Biomedical Research Institute, Valencia, Spain TMAP Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, Department of Medicine, University of Valencia, Valencia, Spain Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
Joan Vila-Francés
Affiliation:
Intelligent Data Analysis Laboratory (IDAL), University of Valencia, Spain
Diego Macias Saint-Gerons
Affiliation:
Center for Biomedical Research in Mental Health Network (CIBERSAM), ISCIII, Madrid, Spain INCLIVA Biomedical Research Institute, Valencia, Spain TMAP Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, Department of Medicine, University of Valencia, Valencia, Spain
Constanza San-Martín
Affiliation:
Center for Biomedical Research in Mental Health Network (CIBERSAM), ISCIII, Madrid, Spain INCLIVA Biomedical Research Institute, Valencia, Spain TMAP Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, Department of Medicine, University of Valencia, Valencia, Spain Department of Physiotherapy, University of Valencia, Valencia, Spain
Rosa Ayesa-Arriola
Affiliation:
Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
Rafael Tabarés-Seisdedos
Affiliation:
Center for Biomedical Research in Mental Health Network (CIBERSAM), ISCIII, Madrid, Spain INCLIVA Biomedical Research Institute, Valencia, Spain TMAP Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, Department of Medicine, University of Valencia, Valencia, Spain Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
*
*Authors for correspondence: Patricia Correa-Ghisays, E-mail: [email protected] Vicent Balanzá-Martínez, E-mail: [email protected]
*Authors for correspondence: Patricia Correa-Ghisays, E-mail: [email protected] Vicent Balanzá-Martínez, E-mail: [email protected]

Abstract

Background

Characterizing neurocognitive endophenotypes of mental illnesses (MIs) could be useful for identifying at-risk individuals, increasing early diagnosis, improving disease subtyping, and proposing therapeutic strategies to reduce the negative effects of the symptoms, in addition to serving as a scientific basis to unravel the physiopathology of the disease. However, a standardized algorithm to determine cognitive endophenotypes has not yet been developed. The main objective of this study was to present a method for the identification of endophenotypes in MI research.

Methods

For this purpose, a 14-expert working group used a scoping review methodology and designed a method that includes a scoring template with five criteria and indicators, a strategy for their verification, and a decision tree.

Conclusions

This work is ongoing since it is necessary to obtain external validation of the applicability of the method in future research.

Keywords

Mental illnessmethodology designneurocognitive endophenotype
Type
Research Article
Information
European Psychiatry , Volume 65 , Issue 1 , 2022 , e85
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is used to distribute the re-used or adapted article and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use.
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the European Psychiatric Association

Introduction

The concept of “endophenotype” was coined in 1966 by Bernard John and Kenneth R. Lewis in a study of the chromosomal and geographical variability of grasshoppers [Reference John and Lewis1]. Later, this term has been used in multiple fields of medicine to clarify the etiology and pathophysiology of various clinical conditions. The endophenotype, also called the intermediate phenotype, has been used in many ways, mostly to refer to a phenotype that is closer to the biological etiology of the disorders than to the signs or symptoms affected by one or more genes associated with the disease [Reference Gottesman and Gould2]. Specifically, in psychiatry, endophenotypes acquired special relevance when they began to be associated with cognitive functioning [Reference Gottesman and Gould2] and were used to help understand the genomics of schizophrenia and other mental illnesses (MIs), becoming an excellent potential tool for multiple studies in neurobiology, neuropsychiatry, neuropsychology, and heritability [Reference Braff and Tamminga3–Reference Toniolo, Fernandes, Silva, da Silva Dias and Lafer5]. An increasing number of studies have included this concept as the basis for their research, using neurocognitive evaluations instead of genetic and brain morphology tests to identify cognitive endophenotypes [Reference Kim, Kim, Koo, Yun and Won6–Reference Van Rheenen, Lewandowski, Lipschitz and Burdick10].

Several criteria have been proposed to establish that a specific characteristic can be considered an endophenotype of pathology. For instance, it must appear concomitantly with the pathology to be studied; that is, it can be considered as an element of the disease in question, although it is not necessarily a requirement of it but has a high probability of manifesting itself [Reference Faraone, Taylor and Tsuang11, Reference Freedman, Adler and Leonard12]. Another criterion that should be taken into account for the determination of an endophenotype is that it should be “measurable” and “temporarily stable”; that is, it should be more of a “trait marker” than a “state marker” of the disease [Reference Doyle, Wozniak, Wilens, Henin, Seidman and Petty13, Reference Vieta14]. Moreover, an endophenotype must be observable in subsequent measurements, thus introducing a longitudinal perspective in the search for and verification of endophenotypes [Reference Vieta14, Reference Glahn, Knowles, McKay, Sprooten, Raventós and Blangero15]. Furthermore, the presence of similar deficits in the unaffected biological relatives of these individuals favors the use of a genetic substrate for them [Reference Balanzá-Martínez, Rubio, Selva-Vera, Martinez-Aran, Sanchez-Moreno and Salazar-Fraile16–Reference Samamé, Martino and Strejilevich20].

The most commonly used criteria to identify endophenotypes in recent clinical studies are as follows: The phenotype (a) is associated with illness in the population, (b) is heritable, (c) is state-independent (manifests in an individual whether or not the illness is active) but age-normed and might need to be elicited by a challenge, (d) co-segregates with the illness within families, and (e) one of which identified in the proband is found in the unaffected relatives at a higher rate than in the general population [Reference Hasler, Drevets, Gould, Gottesman and Manji21].

In the case of neurocognitive endophenotypes, various studies using several of these criteria have shown that there are neurocognitive deficits in the broad domains of attention, memory, and executive functions in patients with MIs, such as bipolar disorder (BD) or schizophrenia, as well as in their first-degree relatives (FDRs), although the latter in an attenuated manner [Reference Arts, Jabben, Krabbendam and van Os22–Reference Volkert, Schiele, Kazmaier, Glaser, Zierhut and Kopf26]. Similarly, complex polygenicity with a predominance of the genetic component has been established by studies including twins and FDR, facilitating the search for cognitive endophenotypes linked to MIs. However, the outright neurocognitive endophenotypes associated with MIs remain unclear. Moreover, a consensual and standardized cognitive evaluation and selection procedure that allows identification and a more comprehensive description of the cognitive endophenotypes associated with MIs are not available yet [Reference Bourne, Aydemir, Balanzá‐Martínez, Bora, Brissos and Cavanagh27–Reference Maekawa, Katsuki, Kishimoto, Onitsuka, Ogata and Yamasaki29].

Studies on endophenotypes constitute a cost-effective and easier method to implement when studying the wide range of subclinical characteristics of MIs [Reference Balanzá-Martínez, Rubio, Selva-Vera, Martinez-Aran, Sanchez-Moreno and Salazar-Fraile16, Reference Balanza-Martinez, Crespo-Facorro, Gonzalez-Pinto and Vieta23, Reference Cardoso, Bauer, Meyer, Kapczinski and Soares30–Reference Tabarés-Seisdedos, Balanzá-Martínez, Sánchez-Moreno, Martinez-Aran, Salazar-Fraile and Selva-Vera32]. Characterizing endophenotypic profiles associated with MIs could be useful for identifying individuals at risk, increasing the effectiveness of early diagnosis, improving disease subtyping, and proposing therapeutic strategies to reduce the negative effects of the symptoms, in addition to serving as a scientific basis for the physiopathology of the disease [Reference Mora, Portella, Forcada, Vieta and Mur33–Reference Torrent, Martinez-Arán, del Mar Bonnin, Reinares, Daban and Solé35]. Thus, the identification of suitable cognitive endophenotypes for MIs is a potentially useful strategy to improve the understanding of MIs [Reference Dias, Balanzá‐Martinez, Soeiro‐de‐Souza, Moreno, Figueira and Machado‐Vieira36–Reference Russo, Mahon, Shanahan, Ramjas, Solon and Braga39].

Due to the discrepancies found in the procedures and criteria used to identify the cognitive endophenotypes of a MI and in the results on what can be considered a stable cognitive endophenotype of a certain MI, we consider that there is a need for a standardized method that provides definite and clear neuroscientific support for cognitive endophenotypic profiling in future research. The main objective of this study was to present a method that includes and refines the procedures used by other researchers for the search and identification of suitable cognitive endophenotypes in MI research, for each individual diagnosis or for identification of common endophenotypes across multiple diagnoses. We propose an inventory of exploration and verification, which in addition to fulfilling its primary objective, could be useful in unifying the results of previous studies in future investigations.

Methods

Scoping review

We conducted a scoping review (PRISMA-ScR) [Reference Tricco, Lillie, Zarin, O’Brien, Colquhoun and Levac40], which is the most widely used method for synthesizing research evidence when the subject has not yet been extensively reviewed or is complex or heterogeneous in nature. The method is mostly used when researchers seek, among other things, to identify research gaps in the existing literature and attempt to develop a methodological framework for rigorously and transparently mapping the area being investigated [Reference Pham, Rajić, Greig, Sargeant, Papadopoulos and McEwen41], as in our case. The scoping review protocol was accomplished by the members of the research team CB/07/09/0021 of the Center for Biomedical Research in Mental Health Network (CIBERSAM).

The following search string was used on the “Scopus,” “Web of Science,” and “PubMed/Medline” databases: (endophenotype OR intermediate phenotype) AND (mental disorder OR MI OR psychiatric disorder OR psychiatric illness) AND (cognitive OR neurocognitive) AND (first degree OR relatives). The following main filters were applied at convenience: Full text, article records from inception to July 31, 2022, English, and Humans. The inclusion criteria were original articles that focused on the identification of cognitive or neurocognitive endophenotypes of MIs that include any of the following aspects: (a) Studies on patients with a psychiatric disorder and healthy controls; (b) Studies on patients with a psychiatric disorder and relatives of patients; (c) Studies on patients with a psychiatric disorder, relatives of patients, and healthy controls; (d) Studies on the relatives of patients with a psychiatric disorder and healthy controls; and (e) Studies on patients with different types of psychiatric diseases compared with each other. The exclusion criteria were: (a) Studies focused on different types of endophenotypes, such as genetic, physiological, neurological, brain structure, or other health aspects; (b) Studies where only one or several cognitive functions were evaluated in psychiatric patients, without considering the endophenotypic aspect; and (c) Studies not relevant to the study objective.

Method design

A working team of 14 experts from different Spanish research groups was established to design the cognitive endophenotype identification method in four steps. First, a criteria list was established based on the most used criteria found through scoping review. Second, each criterion was defined based on its background. Third, each indicator was established; that is, the manifest properties by which each criterion can be directly identified and measured. Fourth, based on the know-how of experts, group decisions were made considering the importance of each criterion and indicator. The weight or value that each would have, and the method to rate them and verify the endophenotype were considered to set up a scoring system to obtain numerical data. The scoring system can be used to statistically analyze the results in future studies.

To provide content and construct validity, each expert separately evaluated the relevance, coherence, sufficiency, clarity, and weight, of each element of the method based on: general procedure, aspects to consider during the process, criterion, definition, indicator, score, and verification of the criteria, verification of the endophenotype, and the decision tree. Inter-rater reliability was used to score this process.

Results

Scoping review

Following the search string, a total of 5,176 papers were retrieved from the databases (2,114 from PubMed/Medline, 1,763 from Scopus, and 1,299 from Web of Science) as potential papers for inclusion in the study. After applying the filters, removing duplicates, and unifying and refining the searches of each reviewer, 2,620 articles were excluded. The results of the selected 2,556 publications were screened and evaluated, and were further refined based on whether they described the use of a methodology to identify cognitive endophenotypes of psychiatric diseases. Finally, 83 papers were included in this study (Figure 1).

Analyzing the selection criteria of neurocognitive endophenotypes used in the studies, it was found that, the diseases included attention deficit hyperactivity disorder (k = 11), anorexia nervosa (k = 3), autism spectrum disorder (k = 2), BD (k = 21), eating disorders (k = 3), mood disorders (k = 6), obsessive–compulsive disorder (k = 9), substance use disorder (k = 2), schizophrenia, and psychosis spectrum (k = 30), and others. Unaffected relatives in comparison with genetically unrelated controls were included in the 83 studies. Eighty-one of the papers compared a group of patients with healthy controls. At least two repeated measures were included in four studies. Age-normed and clinical variables that could affect the performance were considered in statistical analyses of 55 of the studies.

Based on these findings a list of the “most used criteria” and its “indicators” were configured:

  1. 1. Concomitance or association with the disease, high probability of manifestation, and measurability: comparison with other groups.

  2. 2. Presence in biological relatives, heritability, or co-segregation with the disease within families: inclusion of unaffected relatives in comparison with genetically unrelated controls in the study.

  3. 3. Temporary stability (longitudinal perspective): longitudinal studies with at least two repeated measures.

  4. 4. State independence: age-normed and clinical variables that could affect performance considered in statistical analyses.

The 83 articles summarizing the target groups, endophenotypes studied, and selection criteria used, are arranged in chronological order in Table 1.

Table 1. Summary of the included articles.

Abbreviations: ADHD, attention deficit hyperactivity disorder; AN, anorexia nervosa; ASD, autism spectrum disorder; BD, bipolar disorder; ED, eating disorders; MD, mood disorders; OCD, obsessive–compulsive disorder; SUD, substance use disorder; SZ, schizophrenia and psychosis spectrum.

a Most used criteria: 1 = Concomitance or association with the disease, high probability of manifesting itself, and measurability; 2 = Presence in biological relatives, heritability, or co-segregation with the disease within families; 3 = Temporary stability (longitudinal perspective); 4 = State independence.

In summary, most of the articles reviewed and evidenced the existence of endophenotypes in individuals diagnosed with MIs and their FDR compared with healthy controls, fulfilling the first and second criteria. Very few of them included repeated measures regarding the third criterion. As to the fourth criterion, although in most of the articles some sociodemographic and clinical variables were controlled, they did not control the effect of some of them that might have given rise to interpretation biases and reduced the power of the findings. Additionally, none of them considered these a useful criterion for the selection of endophenotypes. Another important aspect is that very few studies corroborated their findings on a certain endophenotype based on the same description of a specific cognitive function and/or with the same measurement instrument or even the same clinical type as in other studies.

The designed method

The final version of the method was obtained after refining each of the four steps through a cross-review among the experts. The consensus included five classification categories or criteria: (a) association, (b) heritability, (c) stability, (d) independence, and (e) reliability of results with corresponding descriptions, each with indicators and corresponding weightage and a particular verification system. Although these five categories include the previously used criteria, some modifications were made in terms of their definition and indicators that identify them. For example, the “heritability” criterion synthesizes the following: the endophenotype is heritable, co-segregates within families, and can be seen in unaffected relatives. This criterion also includes a new indicator—the profile or an intermediate pattern of family members’ performance compared with individuals with particular MI and healthy controls [Reference Kim, Kim, Koo, Yun and Won6, Reference Frantom, Allen and Cross67, Reference Islam, Habtewold, van Es, Quee, van den Heuvel and Alizadeh124]. We also added a new criterion, “reliability of results,” referring to corroboration of the findings with those of previous studies because although these criteria are generally reflected in studies of this type, they are not specifically referred to as selection criteria.

Finally, the method with five deliveries was generated: (a) a general procedure and aspects to consider; (b) a reclassification of five criteria, each with its own definition, indicators, and scoring system; (c) verification of the criteria; (d) verification of the endophenotype (Table 2); and (e) a decision tree (Figure 2).

Table 2. MICEmi scoring template.

Figure 2. Decision tree.

Discussion

In recent years, the interest in cognitive endophenotypes related to MI has increased, causing a change from the previous paradigm—which considers the alterations in MIs as irreversible and that treatments are exclusively curative—toward a new paradigm that focuses on the prevention of those impairments. However, its application is hampered by the lack of a consensus, standardized cognitive evaluation, and selection procedure that allows the identification and a more comprehensive description of the cognitive factors associated with MIs. The use of a method to verify specific criteria to study cognitive endophenotypes in a population with MIs can provide some valuable advantages for researchers, such as systematization, replicability, convergence between different clinical findings, and the delimitation of cognitive endophenotypes for each disease.

The proposed method in this study offers a systematic way of identifying and replicating endophenotypes and therefore should be interpreted as a starting point where the primary goal is the exchange of points of view and subsequent contributions to enrich this field of knowledge and to approach the complexity of reality in a more structured way.

In future research, in addition to the criteria that have already been used to identify cognitive endophenotypes in MIs, it is necessary to add other aspects to the analyses that have not always been studied for further improvement. First, to avoid possible misinterpretations of what is being measured, the same test should be performed to measure each cognitive function, or the results of different tests should be comparable in the most valid and reliable way possible. Second, a greater number of repeated measurements should be made with intermediate time intervals, not so close that they generate a training or learning effect but not so distant that they cause a significant decrease in the sample number. Third, whenever possible, three study groups should be included, including patients with MI, relatives, and controls. Fourth, the maximum number of sociodemographic, psychosocial, clinical, and biological factors should be included to rule out any other possible influences on the cognitive function evaluated other than the biological and genetic factors themselves. Lastly, as we propose in our method as the fifth criterion, “reliability of results,” the findings should be corroborated by previous studies.

This work is ongoing, because it is necessary to obtain external validation of the applicability of the method in future research.

Author Contribution

P C-G: had the original idea; conception and design of the study; co-direct the work team; co-coordinated the scoping review; acquisition and analysis of data for the scoping review; drafting the manuscript and figures. JV S-O: conception and design of the study; co-coordinated the scoping review; acquisition and analysis of data for the scoping review; drafting the manuscript and figures. R T-S; V B-M: co-direct the work team; drafting the manuscript and figures. I F-D, A M-A, JC R-R, G S-V, J V-F, D M-SG, C S-M, R A-A: work team member; drafting the manuscript and figures. L R-B, P C-E: acquisition and analysis of data for the scoping review. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The data supporting the findings of this study are available from the corresponding authors upon reasonable request.

Acknowledgments

Thanks to all those who have helped in carrying out the research.

Financial Support

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Conflicts of Interest

The authors declare none.

Footnotes

P.C.-G. and J.V.S.-O. contributed equally to this work.

References

John, B, Lewis, KR. Chromosome variability and geographic distribution in insects: chromosome rather than gene variations provide the key to differences among populations. Science. 1966;152:711–21. doi:10.1126/science.152.3723.711.CrossRefGoogle Scholar
Gottesman, II, Gould, TD. The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry. 2003;160:636–45. doi:10.1176/appi.ajp.160.4.636.CrossRefGoogle ScholarPubMed
Braff, DL, Tamminga, CA. Endophenotypes, epigenetics, polygenicity and more: Irv Gottesman’s dynamic legacy. Schizophr Bull. 2017;43:10–16. doi:10.1093/schbul/sbw157.CrossRefGoogle Scholar
Miskowiak, KW, Kjaerstad, HL, Meluken, I, Petersen, JZ, Maciel, BR, Köhler, CA, et al. The search for neuroimaging and cognitive endophenotypes: a critical systematic review of studies involving unaffected first-degree relatives of individuals with bipolar disorder. Neurosci Biobehav Rev. 2017;73:1–22. doi:10.1016/j.neubiorev.2016.12.011.CrossRefGoogle ScholarPubMed
Toniolo, RA, Fernandes, FD, Silva, M, da Silva Dias, R, Lafer, B. Cognitive effects of creatine monohydrate adjunctive therapy in patients with bipolar depression: results from a randomized, double-blind, placebo-controlled trial. J Affect Disord. 2017;224:69–75. doi:10.1016/j.jad.2016.11.029.CrossRefGoogle ScholarPubMed
Kim, D, Kim, J, Koo, T, Yun, H, Won, S. Shared and distinct neurocognitive endophenotypes of schizophrenia and psychotic bipolar disorder. Clin Psychopharmacol Neurosci. 2015;13:94. doi:10.9758/cpn.2015.13.1.94.CrossRefGoogle ScholarPubMed
Sanchez‐Moreno, J, Bonnin, CD, González‐Pinto, A, Amann, BL, Solé, B, Balanzá‐Martinez, V, et al. Factors associated with poor functional outcome in bipolar disorder: sociodemographic, clinical, and neurocognitive variables. Acta Psychiatr Scand. 2018;138:145–54. doi:10.1111/acps.12894.CrossRefGoogle ScholarPubMed
Tatay-Manteiga, A, Correa-Ghisays, P, Cauli, O, Kapczinski, FP, Tabarés-Seisdedos, R, Balanzá-Martínez, V. Staging, neurocognition and social functioning in bipolar disorder. Front Psychiatry. 2018;9:709. doi:10.3389/fpsyt.2018.00709.CrossRefGoogle ScholarPubMed
Tatay-Manteiga, A, Cauli, O, Tabarés-Seisdedos, R, Michalak, EE, Kapczinski, F, Balanzá-Martínez, V. Subjective neurocognition and quality of life in patients with bipolar disorder and siblings. J Affect Disord. 2019;245:283–8. doi:10.1016/j.jad.2018.11.012.CrossRefGoogle ScholarPubMed
Van Rheenen, TE, Lewandowski, KE, Lipschitz, JM, Burdick, KE. Conducting clinical studies targeting cognition in psychiatry: guiding principles and design. CNS Spectr. 2019;24:16–21. doi:10.1017/S1092852918001074.CrossRefGoogle ScholarPubMed
Faraone, SV, Taylor, L, Tsuang, M. The molecular genetics of schizophrenia: an emerging consensus. Expert Rev Mol Med. 2002;4:1–3. doi:10.1017/S1462399402004751.CrossRefGoogle ScholarPubMed
Freedman, R, Adler, LE, Leonard, S. Alternative phenotypes for the complex genetics of schizophrenia. Biol Psychiatry. 1999;45:551–8. doi:10.1016/s0006-3223(98)00321-7.CrossRefGoogle ScholarPubMed
Doyle, AE, Wozniak, J, Wilens, TE, Henin, A, Seidman, LJ, Petty, C, et al. Neurocognitive impairment in unaffected siblings of youth with bipolar disorder. Psychol Med. 2009;39:1253–63. doi:10.1017/S0033291708004832.CrossRefGoogle ScholarPubMed
Vieta, E. The bipolar maze: a roadmap through translational psychopathology. Acta Psychiatr Scand. 2014;129:323–7. doi:10.1111/acps.12270.CrossRefGoogle Scholar
Glahn, DC, Knowles, EE, McKay, DR, Sprooten, E, Raventós, H, Blangero, J, et al. Arguments for the sake of endophenotypes: examining common misconceptions about the use of endophenotypes in psychiatric genetics. Am J Med Genet B Neuropsychiatr Genet. 2014;165:122–30. doi:10.1002/ajmg.b.32221.CrossRefGoogle Scholar
Balanzá-Martínez, V, Rubio, C, Selva-Vera, G, Martinez-Aran, A, Sanchez-Moreno, J, Salazar-Fraile, J, et al. Neurocognitive endophenotypes (endophenocognitypes) from studies of relatives of bipolar disorder subjects: a systematic review. Neurosci Biobehav Rev. 2008;32:1426–38. doi:10.1016/j.neubiorev.2008.05.019.CrossRefGoogle ScholarPubMed
Georgiades, A, Rijsdijk, F, Kane, F, Rebollo-Mesa, I, Kalidindi, S, Schulze, KK, et al. New insights into the endophenotypic status of cognition in bipolar disorder: genetic modelling study of twins and siblings. Br J Psychiatry. 2016;208:539–47. doi:10.1192/bjp.bp.115.167239.CrossRefGoogle ScholarPubMed
Glahn, DC, Almasy, L, Barguil, M, Hare, E, Peralta, JM, Kent, JW, et al. Neurocognitive endophenotypes for bipolar disorder identified in multiplex multigenerational families. Arch Gen Psychiatry. 2010;67:168–77. doi:10.1001/archgenpsychiatry.2009.184.CrossRefGoogle ScholarPubMed
Lim, CS, Baldessarini, RJ, Vieta, E, Yucel, M, Bora, E, Sim, K. Longitudinal neuroimaging and neuropsychological changes in bipolar disorder patients: review of the evidence. Neurosci Biobehav Rev. 2013;37:418–35. doi:10.1016/j.neubiorev.2013.01.003.CrossRefGoogle ScholarPubMed
Samamé, C, Martino, DJ, Strejilevich, SA. Longitudinal course of cognitive deficits in bipolar disorder: a meta-analytic study. J Affect Disord. 2014;164:130–8. doi:10.1016/j.jad.2014.04.028.CrossRefGoogle ScholarPubMed
Hasler, G, Drevets, WC, Gould, TD, Gottesman, II, Manji, HK. Toward constructing an endophenotype strategy for bipolar disorders. Biol Psychiatry. 2006;60:93–105. doi:10.1016/j.biopsych.2005.11.006.CrossRefGoogle ScholarPubMed
Arts, B, Jabben, NE, Krabbendam, L, van Os, J. A 2‐year naturalistic study on cognitive functioning in bipolar disorder. Acta Psychiatr Scand. 2011;123:190–205. doi:10.1111/j.1600-0447.2010.01601.x.CrossRefGoogle Scholar
Balanza-Martinez, V, Crespo-Facorro, B, Gonzalez-Pinto, A, Vieta, E. Bipolar disorder comorbid with alcohol use disorder: focus on neurocognitive correlates. Front Physiol. 2015;6:108. doi:10.3389/fphys.2015.00108.Google ScholarPubMed
Bora, E, Yucel, M, Pantelis, C. Cognitive endophenotypes of bipolar disorder: a meta-analysis of neuropsychological deficits in euthymic patients and their first-degree relatives. J Affect Disord. 2009;113:1–20. doi:10.1016/j.jad.2008.06.009.CrossRefGoogle ScholarPubMed
Luperdi, SC, Tabares-Seisdedos, R, Livianos, L, Vieta, E, Cuesta, MJ, Balanza-Martinez, V. Neurocognitive endophenotypes in schizophrenia and bipolar disorder: a systematic review of longitudinal family studies. Schizophr Res. 2019;210:21–9. doi:10.1016/j.schres.2019.06.014.CrossRefGoogle ScholarPubMed
Volkert, J, Schiele, MA, Kazmaier, J, Glaser, F, Zierhut, KC, Kopf, J, et al. Cognitive deficits in bipolar disorder: from acute episode to remission. Eur Arch Psychiatry Clin Neurosci. 2016;266:225–37. doi:10.1007/s00406-015-0657-2.CrossRefGoogle ScholarPubMed
Bourne, C, Aydemir, Ö, Balanzá‐Martínez, V, Bora, E, Brissos, S, Cavanagh, JT, et al. Neuropsychological testing of cognitive impairment in euthymic bipolar disorder: an individual patient data meta‐analysis. Acta Psychiatr Scand. 2013;128:149–62. doi:10.1111/acps.12133.CrossRefGoogle Scholar
Lage, GM, Malloy-Diniz, LF, Neves, FS, Gallo, LG, Valentini, AS, Corrêa, H. A kinematic analysis of manual aiming control on euthymic bipolar disorder. Psychiatry Res. 2013;208:140–4. doi:10.1016/j.psychres.2012.09.046.CrossRefGoogle ScholarPubMed
Maekawa, T, Katsuki, S, Kishimoto, J, Onitsuka, T, Ogata, K, Yamasaki, T, et al. Altered visual information processing systems in bipolar disorder: evidence from visual MMN and P3. Front Hum Neurosci. 2013;7:403. doi:10.3389/fnhum.2013.00403.CrossRefGoogle ScholarPubMed
Cardoso, T, Bauer, IE, Meyer, TD, Kapczinski, F, Soares, JC. Neuroprogression and cognitive functioning in bipolar disorder: a systematic review. Curr Psychiatry Rep. 2015;17:1–24. doi:10.1007/s11920-015-0605-x.CrossRefGoogle ScholarPubMed
Nehra, R, Grover, S, Sharma, S, Sharma, A, Sarkar, S. Neuro-cognitive functioning in unaffected siblings of patients with bipolar disorder: comparison with bipolar patients and healthy controls. Indian J Psychiatry. 2014;56:283. doi:10.4103/0019-5545.140645.CrossRefGoogle ScholarPubMed
Tabarés-Seisdedos, R, Balanzá-Martínez, V, Sánchez-Moreno, J, Martinez-Aran, A, Salazar-Fraile, J, Selva-Vera, G, et al. Neurocognitive and clinical predictors of functional outcome in patients with schizophrenia and bipolar I disorder at one-year follow-up. J Affect Disord. 2008;109:286–99. doi:10.1016/j.jad.2007.12.234.CrossRefGoogle ScholarPubMed
Mora, E, Portella, MJ, Forcada, I, Vieta, E, Mur, M. Persistence of cognitive impairment and its negative impact on psychosocial functioning in lithium-treated, euthymic bipolar patients: a 6-year follow-up study. Psychol Med. 2013;43:1187–96. doi:10.1017/S0033291712001948.CrossRefGoogle ScholarPubMed
Santos, JL, Aparicio, A, Bagney, A, Sánchez‐Morla, EM, Rodríguez‐Jiménez, R, Mateo, J, et al. A five‐year follow‐up study of neurocognitive functioning in bipolar disorder. Bipolar Disord. 2014;16:722–31. doi:10.1111/bdi.12215.CrossRefGoogle ScholarPubMed
Torrent, C, Martinez-Arán, A, del Mar Bonnin, C, Reinares, M, Daban, C, Solé, B, et al. Long-term outcome of cognitive impairment in bipolar disorder. J Clin Psychiatry. 2012;73:10736. doi:10.4088/JCP.11m07471.CrossRefGoogle ScholarPubMed
Dias, VV, Balanzá‐Martinez, V, Soeiro‐de‐Souza, MG, Moreno, RA, Figueira, ML, Machado‐Vieira, R, et al. Pharmacological approaches in bipolar disorders and the impact on cognition: a critical overview. Acta Psychiatr Scand. 2012;126:315–31. doi:10.1111/j.1600-0447.2012.01910.x.CrossRefGoogle ScholarPubMed
Kerner, B. Toward a deeper understanding of the genetics of bipolar disorder. Front Psychiatry. 2015;6:105. doi:10.3389/fpsyt.2015.00105.CrossRefGoogle Scholar
Lee, RS, Hermens, DF, Scott, J, Redoblado-Hodge, MA, Naismith, SL, Lagopoulos, J, et al. A meta-analysis of neuropsychological functioning in first-episode bipolar disorders. J Psychiatr Res. 2014;57:1–11. doi:10.1016/j.jpsychires.2014.06.019.CrossRefGoogle ScholarPubMed
Russo, M, Mahon, K, Shanahan, M, Ramjas, E, Solon, C, Braga, RJ, et al. Affective temperaments and neurocognitive functioning in bipolar disorder. J Affect Disord. 2014;169:51–6. doi:10.1016/j.jad.2014.07.038.CrossRefGoogle ScholarPubMed
Tricco, AC, Lillie, E, Zarin, W, O’Brien, KK, Colquhoun, H, Levac, D, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018;169:467–73. doi:10.7326/M18-0850.CrossRefGoogle ScholarPubMed
Pham, MT, Rajić, A, Greig, JD, Sargeant, JM, Papadopoulos, A, McEwen, SA. A scoping review of scoping reviews: advancing the approach and enhancing the consistency. Res Synth Methods. 2014;5:371–85. doi:10.1002/jrsm.1123.CrossRefGoogle ScholarPubMed
Page, MJ, McKenzie, JE, Bossuyt, PM, Boutron, I, Hoffmann, TC, Mulrow, CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst Rev. 2021;10. doi:10.1186/s13643-021-01626-4.CrossRefGoogle ScholarPubMed
Seidman, LJ, Biederman, J, Monuteaux, MC, Weber, W, Faraone, SV. Neuropsychological functioning in nonreferred siblings of children with attention deficit/hyperactivity disorder. J Abnorm Psychol. 2000;109:252. doi:10.1037/0021-843X.109.2.252.CrossRefGoogle ScholarPubMed
Dollfus, S, Lombardo, C, Bénali, K, Halbecq, I, Abadie, P, Marié, RM, et al. Executive/attentional cognitive functions in schizophrenic patients and their parents: a preliminary study. Schizophr Res. 2002;53:93–9. doi:10.1016/s0920-9964(01)00156-6.CrossRefGoogle ScholarPubMed
Myles‐Worsley, M, Park, S. Spatial working memory deficits in schizophrenia patients and their first degree relatives from Palau, Micronesia. Am J Med Genet. 2002;114:609–15. doi:10.1002/ajmg.10644.CrossRefGoogle ScholarPubMed
Glahn, DC, Therman, S, Manninen, M, Huttunen, M, Kaprio, J, Lönnqvist, J, et al. Spatial working memory as an endophenotype for schizophrenia. Biol Psychiatry. 2003;53:624–6. doi:10.1016/s0006-3223(02)01641-4.CrossRefGoogle ScholarPubMed
Tuulio-Henriksson, A, Arajärvi, R, Partonen, T, Haukka, J, Varilo, T, Schreck, M, et al. Familial loading associates with impairment in visual span among healthy siblings of schizophrenia patients. Biol Psychiatry. 2003;54:623–8. doi:10.1016/s0006-3223(03)00232-4.CrossRefGoogle ScholarPubMed
Slaats-Willemse, D, Swaab-Barneveld, H, De Sonneville, L, Van Der Meulen, E, Buitelaar, JA. Deficient response inhibition as a cognitive endophenotype of ADHD. J Am Acad Child Adolesc Psychiatry. 2003;42:1242–8. doi:10.1097/00004583-200310000-00016.CrossRefGoogle ScholarPubMed
Nicol Ferrier, I, Chowdhury, R, Thompson, JM, Watson, S, Young, AH. Neurocognitive function in unaffected first‐degree relatives of patients with bipolar disorder: a preliminary report. Bipolar Disord. 2004;6:319–22. doi:10.1111/j.1399-5618.2004.00122.x.CrossRefGoogle Scholar
Wittorf, A, Klingberg, S, Wiedemann, G. Secondary verbal memory: a potential endophenotype of schizophrenia. J Psychiatr Res. 2004;38:601–12. doi:10.1016/j.jpsychires.2004.03.005.CrossRefGoogle ScholarPubMed
Stins, JF, Van Baal, GC, Polderman, TJ, Verhulst, FC, Boomsma, DI. Heritability of Stroop and flanker performance in 12-year old children. BMC Neurosci. 2004;5:1–8. doi:10.1186/1471-2202-5-49.CrossRefGoogle ScholarPubMed
Kamarajan, C, Porjesz, B, Jones, KA, Choi, K, Chorlian, DB, Padmanabhapillai, A, et al. Alcoholism is a disinhibitory disorder: neurophysiological evidence from a Go/No-Go task. Biol Psychology. 2005;69:35373. doi:10.1016/j.biopsycho.2004.08.004.CrossRefGoogle ScholarPubMed
Pirkola, T, Tuulio-Henriksson, A, Glahn, D, Kieseppä, T, Haukka, J, Kaprio, J, et al. Spatial working memory function in twins with schizophrenia and bipolar disorder. Biol Psychiatry. 2005;58:930–6. doi:10.1016/j.biopsych.2005.05.041.CrossRefGoogle ScholarPubMed
Calkins, ME, Gur, RC, Ragland, JD, Gur, RE. Face recognition memory deficits and visual object memory performance in patients with schizophrenia and their relatives. Am J Psychiatry. 2005;162:1963–6. doi:10.1176/appi.ajp.162.10.1963.CrossRefGoogle ScholarPubMed
Clark, L, Sarna, A, Goodwin, GM. Impairment of executive function but not memory in first-degree relatives of patients with bipolar I disorder and in euthymic patients with unipolar depression. Am J Psychiatry. 2005;162:1980–2. doi:10.1176/appi.ajp.162.10.1980.CrossRefGoogle Scholar
Holliday, J, Tchanturia, K, Landau, S, Collier, D, Treasure, J. Is impaired set-shifting an endophenotype of anorexia nervosa? Am J Psychiatry. 2005;162:2269–75. doi:10.1176/appi.ajp.162.12.2269.CrossRefGoogle ScholarPubMed
Burdick, KE, Goldberg, JF, Harrow, M, Faull, RN, Malhotra, AK. Neurocognition as a stable endophenotype in bipolar disorder and schizophrenia. J Nerv Ment Dis. 2006;194:255–60. doi:10.1097/01.nmd.0000207360.70337.7e.CrossRefGoogle ScholarPubMed
Wang, Q, Chan, R, Sun, J, Yao, J, Deng, W, Sun, X, et al. Reaction time of the Continuous Performance Test is an endophenotypic marker for schizophrenia: a study of first-episode neuroleptic-naive schizophrenia, their non-psychotic first-degree relatives and healthy population controls. Schizophr Res. 2007;89:293–8. doi:10.1016/j.schres.2006.08.030.CrossRefGoogle ScholarPubMed
Gur, RE, Nimgaonkar, VL, Almasy, L, Calkins, ME, Ragland, JD, Pogue-Geile, MF, et al. Neurocognitive endophenotypes in a multiplex multigenerational family study of schizophrenia. Am J Psychiatry. 2007;164:813–9. doi:10.1176/ajp.2007.164.5.813.CrossRefGoogle Scholar
Ma, X, Wang, Q, Sham, PC, Liu, X, Rabe‐Hesketh, S, Sun, X, et al. Neurocognitive deficits in first‐episode schizophrenic patients and their first‐degree relatives. Am J Med Genet B Neuropsychiatr Genet. 2007;144:407–16. doi:10.1002/ajmg.b.30330.CrossRefGoogle Scholar
Bidwell, LC, Willcutt, EG, DeFries, JC, Pennington, BF. Testing for neuropsychological endophenotypes in siblings discordant for attention-deficit/hyperactivity disorder. Biol Psychiatry. 2007;62:991–8. doi:10.1016/j.biopsych.2007.04.003.CrossRefGoogle ScholarPubMed
Barrantes-Vidal, N, Aguilera, M, Campanera, S, Fatjó-Vilas, M, Guitart, M, Miret, S, et al. Working memory in siblings of schizophrenia patients. Schizophr Res. 2007;95:70–5. doi:10.1016/j.schres.2007.06.020.CrossRefGoogle ScholarPubMed
Menzies, L, Achard, S, Chamberlain, SR, Fineberg, N, Chen, CH, Del Campo, N, et al. Neurocognitive endophenotypes of obsessive-compulsive disorder. Brain. 2007;130:3223–36. doi:10.1093/brain/awm205.CrossRefGoogle ScholarPubMed
Wang, Y, Chan, RC, Yu, X, Shi, C, Cui, J, Deng, Y. Prospective memory deficits in subjects with schizophrenia spectrum disorders: a comparison study with schizophrenic subjects, psychometrically defined schizotypal subjects, and healthy controls. Schizophr Res. 2008;106:70–80. doi:10.1016/j.schres.2007.07.020.CrossRefGoogle ScholarPubMed
Robles, O, Blaxton, T, Adami, H, Arango, C, Thaker, G, Gold, J. Nonverbal delayed recognition in the relatives of schizophrenia patients with or without schizophrenia spectrum. Biol Psychiatry. 2008;63:498–504. doi:10.1016/j.biopsych.2007.05.016.CrossRefGoogle ScholarPubMed
Leppänen, JM, Niehaus, DJ, Koen, L, Du Toit, E, Schoeman, R, Emsley, R. Deficits in facial affect recognition in unaffected siblings of Xhosa schizophrenia patients: evidence for a neurocognitive endophenotype. Schizophr Res. 2008;99:270–3. doi:10.1016/j.schres.2007.11.003.CrossRefGoogle ScholarPubMed
Frantom, LV, Allen, DN, Cross, CL. Neurocognitive endophenotypes for bipolar disorder. Bipolar Disord. 2008;10:387–99. doi:10.1111/j.1399-5618.2007.00529.x.CrossRefGoogle ScholarPubMed
Lopez, C, Tchanturia, K, Stahl, D, Treasure, J. Weak central coherence in eating disorders: a step towards looking for an endophenotype of eating disorders. J Clin Exp Neuropsychol. 2009;31:117–25. doi:10.1080/13803390802036092.CrossRefGoogle ScholarPubMed
Viswanath, B, Reddy, YJ, Kumar, KJ, Kandavel, T, Chandrashekar, CR. Cognitive endophenotypes in OCD: a study of unaffected siblings of probands with familial OCD. Prog Neuropsychopharmacol Biol Psychiatry. 2009;33:610–15. doi:10.1016/j.pnpbp.2009.02.018.CrossRefGoogle ScholarPubMed
Kulkarni, S, Jain, S, Janardhan Reddy, YC, Kumar, KJ, Kandavel, T. Impairment of verbal learning and memory and executive function in unaffected siblings of probands with bipolar disorder. Bipolar Disord. 2010;12:647–56. doi:10.1111/j.1399-5618.2010.00857.x.CrossRefGoogle ScholarPubMed
Tenconi, E, Santonastaso, P, Degortes, D, Bosello, R, Titton, F, Mapelli, D, et al. Set-shifting abilities, central coherence, and handedness in anorexia nervosa patients, their unaffected siblings and healthy controls: exploring putative endophenotypes. The World J Biol Psychiatry. 2010;11:813–23. doi:10.3109/15622975.2010.483250.CrossRefGoogle ScholarPubMed
Chkonia, E, Roinishvili, M, Herzog, MH, Brand, A. First-order relatives of schizophrenic patients are not impaired in the Continuous Performance Test. J Clin Exp Neuropsychol. 2010;32:481–6. doi:10.1080/13803390903201777.CrossRefGoogle Scholar
Wang, Y, Chan, RC, Cui, J, Deng, Y, Huang, J, Li, H, et al. Prospective memory in non-psychotic first-degree relatives of patients with schizophrenia. Psychiatry Res. 2010;179:285–90. doi:10.1016/j.psychres.2009.07.011.CrossRefGoogle ScholarPubMed
Ozan, E, Deveci, E, Oral, M, Karahan, U, Oral, E, Aydın, N, et al. Neurocognitive functioning in a group of offspring genetically at high-risk for schizophrenia in Eastern Turkey. Brain Res Bul. 2010;82:218–23. doi:10.1016/j.brainresbull.2010.04.013.CrossRefGoogle Scholar
Cavedini, P, Zorzi, C, Piccinni, M, Cavallini, MC, Bellodi, L. Executive dysfunctions in obsessive-compulsive patients and unaffected relatives: searching for a new intermediate phenotype. Biol Psychiatry. 2010;67:1178–84. doi:10.1016/j.biopsych.2010.02.012.CrossRefGoogle ScholarPubMed
Calkins, ME, Tepper, P, Gur, RC, Ragland, JD, Klei, L, Wiener, HW, et al. Project among African-Americans to explore risks for schizophrenia (PAARTNERS): evidence for impairment and heritability of neurocognitive functioning in families of schizophrenia patients. Am J Psychiatry. 2010;167:459–72. doi:10.1176/appi.ajp.2009.08091351.CrossRefGoogle ScholarPubMed
Ancin, I, Santos, JL, Teijeira, C, Sánchez‐Morla, EM, Bescós, MJ, Argudo, I, et al. Sustained attention as a potential endophenotype for bipolar disorder. Acta Psychiatr Scand. 2010;122:235–45. doi:10.1111/j.1600-0447.2009.01532.x.CrossRefGoogle ScholarPubMed
Gau, SS, Shang, CY. Executive functions as endophenotypes in ADHD: evidence from the Cambridge Neuropsychological Test Battery (CANTAB). J Child Psychol Psychiatry. 2010;51:838–49. doi:10.1111/j.1469-7610.2010.02215.x.CrossRefGoogle ScholarPubMed
Eack, SM, Mermon, DE, Montrose, DM, Miewald, J, Gur, RE, Gur, RC, et al. Social cognition deficits among individuals at familial high risk for schizophrenia. Schizophr Bull. 2010;36:1081–8. doi:10.1093/schbul/sbp026.CrossRefGoogle ScholarPubMed
Sumiyoshi, C, Kawakubo, Y, Suga, M, Sumiyoshi, T, Kasai, K. Impaired ability to organize information in individuals with autism spectrum disorders and their siblings. Neurosci Res. 2011;69:252–7. doi:10.1016/j.neures.2010.11.007.CrossRefGoogle ScholarPubMed
Breton, F, Planté, A, Legauffre, C, Morel, N, Adès, J, Gorwood, P, et al. The executive control of attention differentiates patients with schizophrenia, their first-degree relatives and healthy controls. Neuropsychologia. 2011;49:203–8. doi:10.1016/j.neuropsychologia.2010.11.019.CrossRefGoogle ScholarPubMed
Antila, M, Kieseppä, T, Partonen, T, Lönnqvist, J, Tuulio-Henriksson, A. The effect of processing speed on cognitive functioning in patients with familial bipolar I disorder and their unaffected relatives. Psychopathology. 2011;44:40–5. doi:10.1159/000317577.CrossRefGoogle ScholarPubMed
Finke, K, Schwarzkopf, W, Müller, U, Frodl, T, Müller, HJ, Schneider, WX, et al. Disentangling the adult attention-deficit hyperactivity disorder endophenotype: parametric measurement of attention. J Abnorm Psychol. 2011;120:890. doi:10.1037/a0024944.CrossRefGoogle ScholarPubMed
Hu, M, Chen, J, Li, L, Zheng, Y, Wang, J, Guo, X, et al. Semantic fluency and executive functions as candidate endophenotypes for the early diagnosis of schizophrenia in Han Chinese. Neurosci Lett. 2011;502:173–7. doi:10.1016/j.neulet.2011.07.037.CrossRefGoogle ScholarPubMed
Rajender, G, Bhatia, MS, Kanwal, K, Malhotra, S, Singh, TB, Chaudhary, D. Study of neurocognitive endophenotypes in drug‐naïve obsessive–compulsive disorder patients, their first‐degree relatives and healthy controls. Acta Psychiatr Scand. 2011;124:152–61. doi:10.1111/j.1600-0447.2011.01733.x.CrossRefGoogle ScholarPubMed
Shang, CY, Gau, SS. Visual memory as a potential cognitive endophenotype of attention deficit hyperactivity disorder. Psychol Med. 2011;41:2603–14. doi:10.1017/S0033291711000857.CrossRefGoogle ScholarPubMed
Li, B, Sun, JH, Li, T, Yang, YC. Neuropsychological study of patients with obsessive-compulsive disorder and their parents in China: searching for potential endophenotypes. Neurosci Bull. 2012;28:475–82. doi:10.1007/s12264-012-1262-2.CrossRefGoogle ScholarPubMed
Daban, C, Mathieu, F, Raust, A, Cochet, B, Scott, J, Etain, B, et al. Is processing speed a valid cognitive endophenotype for bipolar disorder? J Affect Disord. 2012;139:98–101. doi:10.1016/j.jad.2012.02.028.CrossRefGoogle Scholar
MacAllister, WS, Vasserman, M, Vekaria, P, Miles-Mason, E, Hochsztein, N, Bender, HA. Neuropsychological endophenotypes in ADHD with and without epilepsy. Appl Neuropsychol Child. 2012;1:121–8. doi:10.1080/21622965.2012.709421.CrossRefGoogle ScholarPubMed
Gierski, F, Hubsch, B, Stefaniak, N, Benzerouk, F, Cuervo‐Lombard, C, Bera‐Potelle, C, et al. Executive functions in adult offspring of alcohol‐dependent probands: toward a cognitive endophenotype? Alcohol Clin Exp Res. 2013;37:E356–63. doi:10.1111/j.1530-0277.2012.01903.x.CrossRefGoogle Scholar
Kanakam, N, Raoult, C, Collier, D, Treasure, J. Set shifting and central coherence as neurocognitive endophenotypes in eating disorders: a preliminary investigation in twins. World J Biol Psychiatry. 2013;14:464–75. doi:10.3109/15622975.2012.665478.CrossRefGoogle ScholarPubMed
Roberts, ME, Tchanturia, K, Treasure, JL. Is attention to detail a similarly strong candidate endophenotype for anorexia nervosa and bulimia nervosa? World J Biol Psychiatry. 2013;14:452–63. doi:10.3109/15622975.2011.639804.CrossRefGoogle ScholarPubMed
Gau, SF, Huang, WL. Rapid visual information processing as a cognitive endophenotype of attention deficit hyperactivity disorder. Psychol Med. 2014;44:435–46. doi:10.1017/S0033291713000640.CrossRefGoogle ScholarPubMed
Park, S, Gooding, DC. Working memory impairment as an endophenotypic marker of a schizophrenia diathesis. Schizophr Res Cogn. 2014;1:127–36. doi:10.1016/j.scog.2014.09.005.CrossRefGoogle ScholarPubMed
Talbot, A, Hay, P, Buckett, G, Touyz, S. Cognitive deficits as an endophenotype for anorexia nervosa: an accepted fact or a need for re‐examination? Int J Eat Disord. 2015;48:15–25. doi:10.1002/eat.22332.CrossRefGoogle ScholarPubMed
Hıdıroğlu, C, Torres, IJ, Er, A, Işık, G, Yalın, N, Yatham, LN, et al. Response inhibition and interference control in patients with bipolar I disorder and first‐degree relatives. Bipolar Disord. 2015;17:781–94. doi:10.1111/bdi.12335.CrossRefGoogle ScholarPubMed
Kosger, F, Essizoglu, A, Baltacioglu, M, Ulkgun, N, Yenilmez, C. Executive function in parents of patients with familial versus sporadic bipolar disorder. Compr Psychiatry. 2015;61:36–41. doi:10.1016/j.comppsych.2015.05.013.CrossRefGoogle ScholarPubMed
Vierck, E, Porter, RJ, Joyce, PR. Facial recognition deficits as a potential endophenotype in bipolar disorder. Psychiatry Res. 2015;230:102–7. doi:10.1016/j.psychres.2015.08.033.CrossRefGoogle ScholarPubMed
Papmeyer, M, Sussmann, JE, Hall, J, McKirdy, J, Peel, A, Macdonald, A, et al. Neurocognition in individuals at high familial risk of mood disorders with or without subsequent onset of depression. Psychol Med. 2015;45:3317–27. doi:10.1017/S0033291715001324.CrossRefGoogle ScholarPubMed
Zhang, L, Dong, Y, Ji, Y, Zhu, C, Yu, F, Ma, H, et al. Dissociation of decision making under ambiguity and decision making under risk: a neurocognitive endophenotype candidate for obsessive–compulsive disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2015;57:60–8. doi:10.1016/j.pnpbp.2014.09.005.CrossRefGoogle Scholar
Liang, S, Deng, W, Wang, Q, Ma, X, Li, M, Brown, MR, et al. Performance of verbal fluency as an endophenotype in patients with familial versus sporadic schizophrenia and their parents. Sci Rep. 2016;6:32597. doi:10.1038/srep32597.CrossRefGoogle ScholarPubMed
Sharma, S, Bhatia, T, Mazumdar, S, Deshpande, SN. Neurological soft signs and cognitive functions: amongst euthymic bipolar I disorder cases, non-affected first degree relatives and healthy controls. Asian J Psychiatr. 2016;22:53–9. doi:10.1016/j.ajp.2016.04.002.CrossRefGoogle ScholarPubMed
Volkert, J, Haubner, J, Kazmaier, J, Glaser, F, Kopf, J, Kittel-Schneider, S, et al. Cognitive deficits in first-degree relatives of bipolar patients: the use of homogeneous subgroups in the search of cognitive endophenotypes. J Neural Transm. 2016;123:1001–11. doi:10.1007/s00702-016-1581-y.CrossRefGoogle Scholar
Correa-Ghisays, P, Balanzá-Martínez, V, Selva-Vera, G, Vila-Francés, J, Soria-Olivas, E, Vivas-Lalinde, J, et al. Manual motor speed dysfunction as a neurocognitive endophenotype in euthymic bipolar disorder patients and their healthy relatives. Evidence from a 5-year follow-up study. J Affect Disord. 2017;215:156–62. doi:10.1016/j.jad.2017.03.041.CrossRefGoogle ScholarPubMed
Gkintoni, E, Pallis, EG, Bitsios, P, Giakoumaki, SG. Neurocognitive performance, psychopathology and social functioning in individuals at high risk for schizophrenia or psychotic bipolar disorder. J Affect Disord. 2017;208:512–20. doi:10.1016/j.jad.2016.10.032.CrossRefGoogle ScholarPubMed
Merikangas, AK, Cui, L, Calkins, ME, Moore, TM, Gur, RC, Gur, RE, et al. Neurocognitive performance as an endophenotype for mood disorder subgroups. J Affect Disord. 2017;215:163–71. doi:10.1016/j.jad.2017.03.021.CrossRefGoogle ScholarPubMed
Tezcan, D, Tumkaya, S, Bora, E. Reversal learning in patients with obsessive-compulsive disorder (OCD) and their unaffected relatives: is orbitofrontal dysfunction an endophenotype of OCD? Psychiatry Res. 2017;252:231–3. doi:10.1016/j.psychres.2017.03.001.CrossRefGoogle ScholarPubMed
Van Eylen, L, Boets, B, Cosemans, N, Peeters, H, Steyaert, J, Wagemans, J, et al. Executive functioning and local‐global visual processing: candidate endophenotypes for autism spectrum disorder? J Child Psychol Psychiatry. 2017;58:258–69. doi:10.1111/jcpp.12637.CrossRefGoogle ScholarPubMed
Eddy, CM, Cavanna, AE. Set-shifting deficits: a possible neurocognitive endophenotype for Tourette syndrome without ADHD. J Atten Disord. 2017;21:824–34. doi:10.1177/1087054714545536.CrossRefGoogle ScholarPubMed
Bey, K, Kaufmann, C, Lennertz, L, Riesel, A, Klawohn, J, Heinzel, S, et al. Impaired planning in patients with obsessive-compulsive disorder and unaffected first-degree relatives: evidence for a cognitive endophenotype. J Anxiety Disord. 2018;57:24–30. doi:10.1016/j.janxdis.2018.05.009.CrossRefGoogle ScholarPubMed
Calafiore, D, Rossell, SL, Van Rheenen, TE. Cognitive abilities in first-degree relatives of individuals with bipolar disorder. J Affect Disord. 2018;225:147–52. doi:10.1016/j.jad.2017.08.029.CrossRefGoogle ScholarPubMed
Fish, S, Toumaian, M, Pappa, E, Davies, TJ, Tanti, R, Saville, CW, et al. Modelling reaction time distribution of fast decision tasks in schizophrenia: evidence for novel candidate endophenotypes. Psychiatry Res. 2018;269:212–20. doi:10.1016/j.psychres.2018.08.067.CrossRefGoogle ScholarPubMed
McCarthy, NS, Badcock, JC, Clark, ML, Knowles, EE, Cadby, G, Melton, PE, et al. Assessment of cognition and personality as potential endophenotypes in the Western Australian family study of schizophrenia. Schizophr Bull. 2018;44:908–21. doi:10.1093/schbul/sbx141.CrossRefGoogle ScholarPubMed
Miskowiak, KW, Larsen, JE, Harmer, CJ, Siebner, HR, Kessing, LV, Macoveanu, J, et al. Is negative self-referent bias an endophenotype for depression? An fMRI study of emotional self-referent words in twins at high vs. low risk of depression. J Affect Disord. 2018;226:267–73. doi:10.1016/j.jad.2017.10.013.CrossRefGoogle ScholarPubMed
Boxhoorn, S, Lopez, E, Schmidt, C, Schulze, D, Hänig, S, Cholemkery, H, et al. Attention as neurocognitive endophenotype of ADHD across the life span: a family study. Eur Arch Psychiatry Clin Neurosci. 2019;269:627–44. doi:10.1007/s00406-019-00993-3.CrossRefGoogle ScholarPubMed
Correa-Ghisays, P, Sánchez-Ortí, JV, Ayesa-Arriola, R, Setién-Suero, E, Balanzá-Martínez, V, Selva-Vera, G, et al. Visual memory dysfunction as a neurocognitive endophenotype in bipolar disorder patients and their unaffected relatives. Evidence from a 5-year follow-up Valencia study. J Affect Disord. 2019;257:31–7. doi:10.1016/j.jad.2019.06.059.CrossRefGoogle ScholarPubMed
Meluken, I, Ottesen, NM, Harmer, CJ, Scheike, T, Kessing, LV, Vinberg, M, et al. Is aberrant affective cognition an endophenotype for affective disorders?–a monozygotic twin study. Psychol Med. 2019;49:987–96. doi:10.1017/S0033291718001642.CrossRefGoogle ScholarPubMed
Grover, S, Nehra, R. Social cognitions in siblings of patients with schizophrenia: a comparison with patients with schizophrenia and healthy controls-a cross-sectional study. Asian J Psychiatr. 2019;43:24–33. doi:10.1016/j.ajp.2019.04.005.Google Scholar
Tikka, DL, Singh, AR, Tikka, SK. Social cognitive endophenotypes in schizophrenia: a study comparing first episode schizophrenia patients and, individuals at clinical-and familial-‘at-risk’ for psychosis. Schizophr Res. 2020;215:157–66. doi:10.1016/j.schres.2019.10.053.CrossRefGoogle ScholarPubMed
Luperdi, SC, Correa-Ghisays, P, Vila-Francés, J, Selva-Vera, G, Salazar-Fraile, J, Cardoner, N, et al. Is processing speed a valid neurocognitive endophenotype in bipolar disorder? Evidence from a longitudinal, family study. J Psychiatr Res. 2021;141:241–7. doi:10.1016/j.jpsychires.2021.07.008.CrossRefGoogle Scholar
Liu, H, Funkhouser, CJ, Langenecker, SA, Shankman, SA. Set shifting and inhibition deficits as potential endophenotypes for depression. Psychiatry Res. 2021;300:113931. doi:10.1016/j.psychres.2021.113931.CrossRefGoogle ScholarPubMed
Abramovitch, A, De Nadai, AS, Geller, DA. Neurocognitive endophenotypes in pediatric OCD probands, their unaffected parents and siblings. Prog Neuropsychopharmacol Biol Psychiatry. 2021;110:110283. doi:10.1016/j.pnpbp.2021.110283.CrossRefGoogle ScholarPubMed
Rodríguez-Martínez, AE, Monroy-Jaramillo, N, Rodríguez-Agudelo, Y, Solís-Vivanco, R. Working memory impairment as an endophenotypic marker in patients with schizophrenia: failures in encoding or maintenance? Neuropsychobiology. 2021;80:352–8. doi:10.1159/000513495.CrossRefGoogle ScholarPubMed
Islam, MA, Habtewold, TD, van Es, FD, Quee, PJ, van den Heuvel, ER, Alizadeh, BZ, et al. Long‐term cognitive trajectories and heterogeneity in patients with schizophrenia and their unaffected siblings. Acta Psychiatr Scand. 2018;138:591–604. doi:10.1111/acps.12961.CrossRefGoogle ScholarPubMed
Figure 0

Figure 1. PRISMA-ScR flow diagram [42].

Figure 1

Table 1. Summary of the included articles.

Figure 2

Table 2. MICEmi scoring template.

Figure 3

Figure 2. Decision tree.

Submit a response

Comments

No Comments have been published for this article.